Search results

Estimates of the UK demand for money function are obtained utilising the Box‐Cox family of power transformations based on a Bank of England adjusted data set for the period 1963I — 1979IV. The functions are subjected to functional and structural stability testing with careful consideration of the resulting error structure. First‐order autocorrelation problems are encountered in the narrow money series Ml and attempts to consider a more flexible dynamic structure are investigated.

The different types of estimators of rational expectations models are surveyed. A key feature is that the model′s solution has to be taken into account when it is estimated. The two ways of doing this, the substitution and errors‐in‐variables methods, give rise to different estimators. In the former case, a generalised least‐squares or maximum‐likelihood type estimator generally gives consistent and efficient estimates. In the latter case, a generalised instrumental variable (GIV) type estimator is needed. Because the substitution method involves more complicated restrictions and because it resolves the solution indeterminacy in a more arbitary fashion, when there are forward‐looking expectations, the errors‐in‐variables solution with the GIV estimator is the recommended combination.

The purpose of this study is to identify the main drivers which can explain the relative success of BRIC countries (i.e. Brazil, Russia, India and China), collectively and individually, in attracting foreign direct investment (FDIs). Unlike previous studies that have identified gross domestic product (GDP) as a major determinant, we find that for the sampling period 1980-2008, social variables (namely, high population growth and educated labor) and political variables account for 40 and 7 per cent of the variance in net inward FDI, respectively, and no importance for economic variables. Interestingly, for a sub-period (1999-2008), we observe the salience of financial (namely, sizable GDP economy, favorable net trade balance and controlled currency risk and sovereign debt risk) determinants of inward FDI (R2 is 44 per cent). On the other hand, when testing individual countries, it seems that FDI determinants are not universal as each country enjoys different characteristics and sources of strengths that attract FDIs. The implication is to focus more on those incentives that the host country is weak in to be able to optimize the amount of FDI flowing in from foreign investors.

Three blocks of variables were examined: economic/financial, social and political variables. The economic/financial variable set expands on a prototype developed by Dunning (1981), which distinguishes three types of influences on inward FDI. First, it suggests some domestic market characteristics to influence FDI. They include the market size and the direction of trade flows. Another set of economic/financial factors includes measure of the host country’s overall financial performance such as the inflation rate and the effectiveness of the service sector. Social factors of the host country are considered an important determinant of FDI. Our social model included: the degree of human capital development, the extent of urbanization, the quality of life and the adequacy of the health-care system. Political factors were also considered. Using the STATA statistical package, we run a regression analysis on our transformed data twice: once over the full sampling period (1980-2008), and a second time using a partial data set covering the past 10 years (1999-2008), after controlling for multicollinearity and other econometric problems.

Regressing net FDI inflows on all financial, social and political variables during the full data series (1980-2008), and after controlling for severe econometric problems, the nested block regression concludes that the social variables account for 40 per cent of the change in net inward FDI, followed by political variables (7 per cent). The nested regression for the past 10-year data series (1999-2008), however, shows the economic/financial variables block and social variables blocks contribute the most to FDI variations (R2 is 44 and 7 per cent, respectively), while political variables appear insignificant. The findings for each individual country show that the four countries have few common determinants.

Our results are not without limitations. Our sample is limited to BRIC countries that had attracted significant FDIs in the past two decades. Testing for a larger set of countries with smaller or less attractive countries included could be useful before any final conclusions can be drawn. Also, this research can be extended to cover the busted 2008-2010 years. It would be interesting if our results still hold in recent down market conditions. For example, in early 2008, there was a big credit crisis in the USA, followed by a universal market crash in September and October due to large financial institutions collapsing, which resulted in the recent bubble explosion. More recently, we witnessed the European financial crisis beginning with the Greece debt default (followed by fears in Spain, Portugal and potentially others).

Overall, our findings suggest that individual countries enjoy different levels of strengths in economic/financial, social and political variables. A country that strives to attract more inward FDI may consider focusing more on those unique country-specific incentives that it is weak in to be able to optimize its intake of FDIs.

The main goal of our paper is to bring updated evidence on the relevant set of incentives which have made the BRIC block the penchant for FDI, and whether these incentives are the same for each of the BRIC countries. Our paper makes three major contributions. First, it expands Mathur and Singh’s (2007) set of explanatory variables, especially to reflect the effect of financial markets and economic conditions (such as currency exchange rate risk, level of real interest rate, size of national debt, sovereign credit rating risk and inflation), new social variables (such as life expectancy at birth, people receptivity to foreign investors and the number of graduate degree holders) and new political variables (host country’s level of restriction on capital repatriation). Second, it brings more updated evidence by using a longer sampling period (1980-2008). Third, we test BRIC as a group and we retest individual BRIC countries. We also ensure that our results are free from econometric (autocorrelation and heteroskedasticity) problems.

The aim of this paper is to present the relationship between climate and tourism development data as an example of an emerging winter and ski tourism destination in Slovakia.

The method aims to discover the relationship through snow-reliability and regression analyses and to further implicate the consequences of such established relationship under a changing (warming) climate.

As a result of the research, the authors can predict that a 1 per cent fall in snow depth and visibility would erode the ski demand by 1.2 and 0.12 per cent, respectively, a 1°C rise of the mean temperature, on the other hand, would indicate a 6 per cent loss of skipass sales. The latter finding translates into a further 6.6 to 19.2 per cent loss of sales on account of the anticipated temperature increases for the twenty-first century. The capacity of the resort for the utmost adaptation strategy, snowmaking, is also to deteriorate with the daytime/fulltime annual good quality production range to reduce from 33/45 days to 10-26/14-34 days, according to the emissions-related warming scenarios and in terms of the commonly available current technology.

The results of the study can help the management of ski resorts to adopt strategies for the future development by taking into account the predicted climatic changes.

This study is the first type of study performed in Slovakia and can contribute to the better understanding of the relationship between climate change and the performance of the ski tourism resorts. It also delivers innovation by considering wet-bulb temperature in snow-reliability analyses and also by coining the “climate elasticity” concept.

The purpose of this paper is to identify significant factors of environmental variables and pollutants that have an effect on PM_2.5 through wavelet and regression analysis.

In order to provide stable data set for regression analysis, multiresolution analysis using wavelets is conducted. For the sampled data, multicollinearity among the independent variables is removed by using principal component analysis and multiple linear regression analysis is conducted using PM_2.5 as a dependent variable.

It is found that few pollutants such as NO₂, NO_x, SO₂, benzene and environmental factors such as ambient temperature, solar radiation and wind direction affect PM_2.5. The regression model developed has high R² value of 91.9 percent, and the residues are stationary and not correlated indicating a sound model.

The research provides a framework for extracting stationary data and other important features such as change points in mean and variance, using the sample data for regression analysis. The work needs to be extended across all areas in India and for various other stationary data sets there can be different factors affecting PM_2.5.

Control measures such as control charts can be implemented for significant factors.

Rules and regulations can be made more stringent on the factors.

The originality of this paper lies in the integration of wavelets with regression analysis for air pollution data.

In the paper we provide new evidence on the predictability of Scandinavian stock returns, when utilizing the determinants of global capital asset pricing. Three factors are extracted by principal components factor analysis. The VARIMAX‐rotated factor loadings matrix clearly suggests the presence of geographically distinguished returns generating factors: Europe, Asia and America. The corresponding factor price series are used as driving forces for the Finnish and Swedish market returns. The results indicate that the predictability of Scandinavian stock returns is significantly improved by the world factors.

The literature is full of studies of production functions with capital and labour aggregate indices, mainly for the economies or manufacturing industries of the USA and Canada. Traditional Cobb‐Douglas and CES specifications treated aggregate labour on the assumption that heterogeneous labour categories were highly substitutable. Berndt and Christensen proposed that a consistent aggregate of diverse labour exists if certain Allen‐Uzawa partial elasticities of substitution (AUES, denoted σij, i, j = factor inputs) are equal.

Develops a habit‐persistence model which is based on the assumption that experience conditions present behaviour and expectations. Notes that the model combines the adaptive expectations hypothesis with the partial adjustment process. Concludes that accurate forecasts for declining regions are produced but the results for growing regions are not significant.

According to officially published statistics, there began in the UK during 1979 some 2,080 stoppages of work due to industrial disputes, involving 4.584 million workers and resulting in 29.474 million working days lost (Department of Employment Gazette, 1980, p. 874). The purpose of this article is to summarise some of the main developments which have occurred over recent years in the economic analysis of strike activity and to illustrate some of the insights provided by economic theories of the collective bargaining process and its breakdown. We begin with a brief survey of the literature which provides a discussion of its major findings and of the limitations of existing studies. In subsequent sections, some basic theoretical concepts are introduced and after a brief discussion of some important elements of bargaining theory these are used in the construction of an alternative model of the breakdown of the collective bargaining process and the occurrence of strikes. In the penultimate section, this alternative model is tested against UK data and in the final section the main findings are summarised.

Agriculture diversification acts as income enhancing as well as distress mitigating strategy. India has witnessed rise in per-capita income which in turn has increased the demand for food particularly high-valued food items but agricultural production has failed to keep pace with the growing demand. The purpose of this paper is to examine spatio-temporal variations in agricultural diversification (AD) in India. Second, the authors try to identify the determinants of AD. Third, the authors examine the convergence hypothesis with reference to agriculture diversification across Indian states.

The study is based on the panel data constituting 20 major states of India during 1990–1991 to 2013–2014. It uses Simpson Diversification Index to measure AD. The heteroskedasticity-corrected panel regression model is applied to find out the determinants of AD. The fixed-effects model is used to examine β-convergence in AD across the sample states. Alternative time series models are applied to examine σ-convergence in AD.

The rising per-capita income and urbanization are driving dietary diversity towards high-valued crops and providing ample opportunity for AD. But poor and inadequate cold storage facility and rising cost of cultivation are posing major hindrance to it. Small land holding and road length have negatively influenced AD which is contrary to the traditional wisdom. The study found divergence in diversification and rising inequality in diversification.

The study is based on secondary data. A primary study to complement this could have been better. It is only based on one country.

Food inflation has serious adverse effect on the society at large. It is necessary to promote AD for controlling food price inflation. Minimum support price provided by the government should be extended to all crops; otherwise, it will fuel inflation. Given the fact fragmentation of land holding is adversely affecting AD, community based farming and consolidation of farm land should be the way forward to improve farmers’ income as well as reduce risk.

To best of the authors’ study, this is the first study that examines determinants of AD and convergence in AD during the high growth period of India.